🥭 w/ citation cff

CITATION.cff

@@ -0,0 +1,10 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+authors:
+  - family-names: Sahu
+    given-names: Subhajit
+    orcid: https://orcid.org/0000-0001-5140-6578
+title: "puzzlef/pagerank-sequential-vs-openmp: Performance of sequential execution based vs OpenMP based PageRank"
+version: 1.0.0
+doi: 10.5281/zenodo.6717302
+date-released: 2022-06-24

README.md

@@ -1,28 +1,14 @@
-Performance of **sequential** execution based vs **OpenMP** based PageRank
-([pull], [CSR]).
+Performance of **sequential** execution based vs **OpenMP** based PageRank ([pull], [CSR]).
 
 This experiment was for comparing the performance between:
 1. Find pagerank using a single thread (**sequential**).
 2. Find pagerank accelerated using **OpenMP**.
 
-Both techniques were attempted on different types of graphs, running each
-technique 5 times per graph to get a good time measure. Number of threads
-for this experiment (using `OMP_NUM_THREADS`) was varied from `2` to `48`.
-**OpenMP** does seem to provide a **clear benefit** for most graphs (except
-for the smallest ones). This speedup is definitely not directly proportional
-to the number of threads, as one would normally expect (Amdahl's law).
-
-Note that there is still room for improvement with **OpenMP** by using
-sequential versions of certain routines instead of OpenMP versions because
-not all calculations benefit from multiple threads (ex.
-["multiply-sequential-vs-openmp"]). Also note that neither approach makes
-use of *SIMD instructions* which are available on all modern hardware.
-
-All outputs are saved in [out](out/) and a small part of the output is listed
-here. Some [charts] are also included below, generated from [sheets]. The input
-data used for this experiment is available at ["graphs"] (for small ones), and
-the [SuiteSparse Matrix Collection]. This experiment was done with guidance
-from [Prof. Dip Sankar Banerjee] and [Prof. Kishore Kothapalli].
+Both techniques were attempted on different types of graphs, running each technique 5 times per graph to get a good time measure. Number of threads for this experiment (using `OMP_NUM_THREADS`) was varied from `2` to `48`. **OpenMP** does seem to provide a **clear benefit** for most graphs (except for the smallest ones). This speedup is definitely not directly proportional to the number of threads, as one would normally expect (Amdahl's law).
+
+Note that there is still room for improvement with **OpenMP** by using sequential versions of certain routines instead of OpenMP versions because not all calculations benefit from multiple threads (ex. ["multiply-sequential-vs-openmp"]). Also note that neither approach makes use of *SIMD instructions* which are available on all modern hardware.
+
+All outputs are saved in [out](out/) and a small part of the output is listed here. Some [charts] are also included below, generated from [sheets]. The input data used for this experiment is available at ["graphs"] (for small ones), and the [SuiteSparse Matrix Collection]. This experiment was done with guidance from [Prof. Dip Sankar Banerjee] and [Prof. Kishore Kothapalli].
 
 <br>
 
@@ -95,6 +81,8 @@ $ ...
 <br>
 
 [![](https://i.imgur.com/5vdxPZ3.jpg)](https://www.youtube.com/watch?v=rKv_l1RnSqs)
+[![DOI](https://zenodo.org/badge/366356464.svg)](https://zenodo.org/badge/latestdoi/366356464)
+
 
 [Prof. Dip Sankar Banerjee]: https://sites.google.com/site/dipsankarban/
 [Prof. Kishore Kothapalli]: https://cstar.iiit.ac.in/~kkishore/

system.txt

@@ -1,5 +1,5 @@
 Dell PowerEdge R740 Rack Mount Chassis
-Proc:  Intel(R) Xeon(R) Silver 4116 CPU @ 2.10GHz (48 cores x 2)
+Proc:  Intel(R) Xeon(R) Silver 4116 CPU @ 2.10GHz (12 cores x 2)
 Cache: L1d+i: 768KB, L2: 12MB, L3: 16MB (shared), NUMA: 2
 Mem:   128GB DIMM DDR4 Synchronous Registered (Buffered) 2666 MHz (8x16GB)
 Disk:  MegaRAID SAS-3 3108 [Invader]; 10TB PERC H730P Adp